For our Client we are looking for an experienced Data Modeller.
📍 Location: Kraków, hybrid work model – 2 days per week in the office, 3 days remote
🕒 Cooperation model: [Full-time / B2B]
📍 Project for our Client from the financial sector
The team
The team's organisation consists of individuals working both on global, regional, and local projects in support of all Global Businesses and Global Functions. The individual(s) in the role of Data Modelling will be responsible for modelling data within specific Businesses, Functions and/or Geographies and will work with the Data CIOs and Data Officers and their respective teams as needed.
The Role
The data modeler designs, implements, and documents data architectures and data models for solutions, which include the use of application, relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, operations, machine learning, data science, and other business interests.
The successful candidate will:
- Be responsible for the development of the conceptual, logical, and physical data models, oversight of the implementation of RDBMS, operational data stores (ODS), application databases, data marts, and data lakes on target platforms (SQL/NoSQL/cloud/on-prem)
- Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively
Responsibilities
- Implement business and IT data requirements through new data strategies and designs across all data platforms (application, relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, operations, and machine learning)
- Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
- Define and govern data modelling and design standards, tools, best practices, and related development for enterprise data models
- Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualisations
- Hands-on modelling, design, configuration, installation, performance tuning, and sandbox POC
- Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks
Requirements:
- 3+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols). Experience on MongoDB would be an advantage
- Good knowledge of metadata management, data modelling, and related tools (Erwin or Visual Paradigm or others) required
- Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre contexts is desired
- Experience in team management, communication, and presentation
- Strong communication skill, good oral English
Why apply for an Antal job offer?
When your application is successful, you will be supported by a dedicated Consultant who will stay in regular contact with you (via email or phone), help you prepare for interviews with your future employer, and ensure a smooth and professional recruitment process.
About Antal
Antal is a leading recruitment and HR advisory company, present in Poland since 1996 and later expanded to the Czech Republic and Hungary. Across the CEE region, we employ around 150 professionals who deliver a full range of services – from specialist and executive recruitment, employee outsourcing and HR consulting, to employer branding and market research.
Our division-based structure combines deep industry expertise with functional specialisation, enabling us to provide tailored solutions for companies in every sector. We act as a trusted partner for both employers and candidates, sharing our knowledge and guiding them through every stage of the talent journey. We connect exceptional people with the right opportunities and help organisations build successful teams.
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